Machine learning assisted plasmonic metascreen for enhanced broadband absorption in ultra-thin silicon films  

作　　者：Waqas W.Ahmed Haicheng Cao Changqing Xu Mohamed Farhat Muhammad Amin Xiaohang Li Xiangliang Zhang Ying Wu 

机构地区：[1]Division of Computer,Electrical and Mathematical Sciences and Engineering,King Abdullah University of Science and Technology(KAUST),Thuwal 23955-6900,Saudi Arabia [2]College of Engineering,Taibah University,Madinah 42353,Saudi Arabia [3]Division of Physical Science and Engineering,King Abdullah University of Science and Technology(KAUST),Thuwal 23955-6900,Saudi Arabia [4]Department of Computer Science and Engineering,University of Notre Dame,NotreDame,IN46556,USA

出　　处：《Light(Science & Applications)》2025年第2期411-421,共11页光(科学与应用)(英文版)

基　　金：supported by King Abdullah University of Science and Technology(KAUST)Artificial Intelligence Initiative Fund,KAUST Baseline Research Fund No.BAS/1/1626-01-01;KAUST Office of the Sponsored Research under grant nos.OSR-2020-CRG9-4374 and OSR-2022-CRG11-5055.

摘　　要：We propose and demonstrate a data-driven plasmonic metascreen that efficiently absorbs incident light over a wide spectral range in an ultra-thin silicon flm.By embedding a double-nanoring silver array within a 20 nm ultrathin amorphous silicon(a-Si)layer,we achieve a significant enhancement of light absorption.This enhancement arises from the interaction between the resonant cavity modes and localized plasmonic modes,requiring precise tuning of plasmon resonances to match the absorption region of the silicon active layer.To facilitate the device design and improve light absorption without increasing the thickness of the active layer,we develop a deep learning framework,which learns to map from the absorption spectra to the design space.This inverse design strategy helps to tune the absorption for selective spectral functionalities.Our optimized design surpasses the bare silicon planar device,exhibiting a remarkable enhancement of over 100%.Experimental validation confirms the broadband enhancement of light absorption in the proposed configuration.The proposed metascreen absorber holds great potential for light harvesting applications and may be leveraged to improve the light conversion effciency of ultra-thin silicon solar cells,photodetectors,and optical filters.

关 键 词：deep learning framework resonant cavity modes machine learning absorbs incident light ultra thin silicon films broadband absorption plasmonic metascreen tuning plasmon resonances 

分 类 号：O469[理学—凝聚态物理]